{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "aa8140dc",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple\n",
      "Collecting matplotlib\n",
      "  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/ad/62/7b662284352867a86acfb636761ba351723fc3a235efd8397578d903413d/matplotlib-3.5.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (11.2 MB)\n",
      "\u001b[K     |████████████████████████████████| 11.2 MB 30.9 MB/s eta 0:00:01\n",
      "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /opt/conda/lib/python3.7/site-packages (from matplotlib) (1.21.2)\n",
      "Collecting cycler>=0.10\n",
      "  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/5c/f9/695d6bedebd747e5eb0fe8fad57b72fdf25411273a39791cde838d5a8f51/cycler-0.11.0-py3-none-any.whl (6.4 kB)\n",
      "Requirement already satisfied: packaging>=20.0 in /opt/conda/lib/python3.7/site-packages (from matplotlib) (21.3)\n",
      "Requirement already satisfied: pillow>=6.2.0 in /opt/conda/lib/python3.7/site-packages (from matplotlib) (8.4.0)\n",
      "Collecting kiwisolver>=1.0.1\n",
      "  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/ab/8f/8dbe2d4efc4c0b08ec67d6efb7cc31fbfd688c80afad85f65980633b0d37/kiwisolver-1.4.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (1.1 MB)\n",
      "\u001b[K     |████████████████████████████████| 1.1 MB 2.3 MB/s eta 0:00:01\n",
      "\u001b[?25hCollecting fonttools>=4.22.0\n",
      "  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/59/73/d8f2d961ecd548685d770fb005e355514573d2108d8ed9460d7a1f1870b5/fonttools-4.37.4-py3-none-any.whl (960 kB)\n",
      "\u001b[K     |████████████████████████████████| 960 kB 881 kB/s eta 0:00:01\n",
      "\u001b[?25hRequirement already satisfied: python-dateutil>=2.7 in /opt/conda/lib/python3.7/site-packages (from matplotlib) (2.8.2)\n",
      "Requirement already satisfied: pyparsing>=2.2.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib) (3.0.8)\n",
      "Requirement already satisfied: typing-extensions in /opt/conda/lib/python3.7/site-packages (from kiwisolver>=1.0.1->matplotlib) (3.10.0.2)\n",
      "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.7/site-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n",
      "Installing collected packages: kiwisolver, fonttools, cycler, matplotlib\n",
      "Successfully installed cycler-0.11.0 fonttools-4.37.4 kiwisolver-1.4.4 matplotlib-3.5.3\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "# %pip install matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9fde34cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import jax.numpy as jnp\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7d949d92",
   "metadata": {},
   "outputs": [],
   "source": [
    "def sigmoid(x):\n",
    "    \"\"\"\n",
    "    implement the activation function of sigmoid\n",
    "    x:the input value\n",
    "    return:the activation value\n",
    "    \"\"\"\n",
    "    return 1/(1+jnp.exp(-x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a92d3175",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define a vector\n",
    "input_val=jnp.arange(-10,10,0.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "470064ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f62280eab10>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(input_val,sigmoid(input_val))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a38f17c1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
